The Agent-to-Agent (A2A) protocol is a new standard by Google that enables AI agents—regardless of their underlying framework or developer—to…
Machine Learning
We introduce a set of training-free ABX-style discrimination tasks to evaluate how multilingual language models represent language identity (form) and…
A widespread strategy for obtaining a language model that performs well in a target domain is to fine-tune it by…
The Importance of Symbolic Reasoning in World Modeling Understanding how the world works is key to creating AI agents that…
End-to-end (E2E) Automatic Speech Recognition (ASR) models are trained using paired audio-text samples that are expensive to obtain, since high-quality…
Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative…
Uncertainty Quantification (UQ) in Language Models (LMs) is key to improving their safety and reliability. Evaluations often use metrics like…
Introduction AI agents are increasingly moving from pure backend automators to visible, collaborative elements within modern applications. However, making agents…
Understanding Subgroup Fairness in Machine Learning ML Evaluating fairness in machine learning often involves examining how models perform across different…
Cybersecurity has become a significant area of interest in artificial intelligence, driven by the increasing reliance on large software systems…
In this tutorial, we’ll build a powerful and interactive Streamlit application that brings together the capabilities of LangChain, the Google…
The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed to understand language but are…
Modern generative AI model providers require unprecedented computational scale, with pre-training often involving thousands of accelerators running continuously for days,…
The AWS DeepRacer Student Portal will no longer be available starting September 15, 2025. This change comes as part of…
As AI adoption accelerates and reshapes our future, organizations are adapting to evolving regulatory frameworks. In our report commissioned to…
In recent years, the rapid advancement of artificial intelligence and machine learning (AI/ML) technologies has revolutionized various aspects of digital…
Accommodating human preferences is essential for creating aligned LLM agents that deliver personalized and effective interactions. Recent work has shown…
Recent research demonstrated that training large language models involves memorization of a significant fraction of training data. Such memorization can…
We study Variational Rectified Flow Matching, a framework that enhances classic rectified flow matching by modeling multi-modal velocity vector-fields. At…
Flow matching models have emerged as a powerful method for generative modeling on domains like images or videos, and even…